After giving an overview (see Part 1), Paul Whelan, of the Imperial College London and formerly the European Central Bank, walked the audience through the mechanics of an award-winning paper on monetary policy at a webinar on January 16, 2014 sponsored by GARP.

A shock, by its very nature, is non-routine. Therefore, “a good measure of monetary policy shocks should exclude systematic components,” Whelan said. Another challenge was to “distinguish between quantity of risk versus price of risk channels.”

Use of the Taylor rule allowed the researchers to isolate the exogenous dynamics of monetary policy. The trio was able to obtain a residual, where the deviations from the rule were attributable to shocks such as 9/11 and oil-market shocks.

Whelan noted there was a wrinkle to “shocks”: sometimes there were targets or expectations.—and if so, he questioned whether these were true shocks. As an example Whelan quoted chairman of the Federal Reserve BoardBen Bernanke, who noted that “Long-term rates … depend primarily not on the current funds rate but on how financial market participants expect the funds rate and other short-term rates to evolve over time.”

For the 2008 financial crisis, the researchers defined “path shocks” to be “exogenous forward guidance shocks.” The study made use of “a very cool set of expectations data,” said Whelan. The BlueChip Financial Forecasts (BCFF) survey consisted of 750,000 data points collected since 1990. The researchers constructed time series of excess returns for bond series, and controlled for macro-economic activity with a proxy for the conditional mean of growth.

Whelan provided details on the investigation into time series dynamics of path shocks, and whether the system could be adequately spanned by the yield curve information available. They compared bond predictability for high-yield bonds for two time periods, 1990-2011, and 1990-2007. They found “almost no correlation” (0.09) during the crisis but “high correlation” (0.43) in the time interval since then.

Additionally, they considered the cross-section of equity returns. They modelled the portfolio for monetary policy path shocks and used a first-pass regression to identify the betas. Second-pass regressions were used to identify the price of risk.

To understand the predictability of the method, Whelan said they examined price versus quantity of risk, and “habit versus long-range risk.” They found very little evidence of habit.

“Data is king,” said Whelan during the final remarks. It was an exciting area to study with the tools and survey data now available. “Twenty years ago, people didn’t care about surveys but we’ve shown you can get a lot of interesting material from them.” ª